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Azure Data Factory
An Azure service for ingesting, preparing, and transforming data at scale.
11,627 questions
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Data Factory in Microsoft Fabric and ADF are both data integration services provided by Microsoft, but they differ in several key aspects:
Purpose and Integration:
- ADF: Primarily designed for data integration, ADF focuses on orchestrating data movement and transformation across diverse sources. It offers robust scheduling, monitoring, and auditing functionalities, enabling users to manage and track data pipelines effectively.
- Data Factory in Microsoft Fabric: Part of the broader Microsoft Fabric ecosystem, this service provides a modern data integration experience that empowers users to ingest, prepare, and transform data from a rich set of data sources. It integrates seamlessly with other Microsoft Fabric components, such as OneLake, Lakehouse, Power BI, and AI services, offering a unified data platform.
User Accessibility and Technical Skills Required:
- ADF: Geared towards data engineers and developers, ADF requires a solid understanding of data engineering concepts. Its interface, while powerful, may present a learning curve for those without a technical background.
- Data Factory in Microsoft Fabric: Designed to be more user-friendly, this service caters to a broader audience, including business users, data engineers, and data scientists. Its modern, low-code interface simplifies data integration tasks, making it accessible to users with varying levels of technical proficiency.
When to Use Each:
- ADF: Suitable for scenarios requiring robust data integration capabilities, especially when working with a wide range of data sources and destinations. It's ideal for complex ETL processes and enterprises with advanced data orchestration needs.
- Data Factory in Microsoft Fabric: Best suited for organizations operating within the Microsoft Fabric ecosystem, particularly when there's a need for seamless integration with tools like Power BI and AI services. Its user-friendly design and advanced analytics capabilities make it ideal for teams seeking an integrated data platform.
Links to help you :
https://learn.microsoft.com/en-us/fabric/data-factory/data-factory-overview
https://casewhen.co/blog/data-factory-showdown-fabric-vs-azure
https://www.linkedin.com/pulse/microsoft-fabric-vs-azure-data-factory-key-differences-uttam--mnrsc/